El precio de acceso a una plataforma de televisión

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Transcript El precio de acceso a una plataforma de televisión

Research problem:
Detecting clusters of
activity in Catalonia
Jenifer Ruiz-Valenzuela
Regional Quantitative Analysis Research Group
Institut d’Economia Aplicada
Regional i Pública
1. Motivation and objectives


Enlargement of the EU to the Central and Eastern European Countries,
Elimination of textile quotas between WTO members.
reinforcement of the relocation processes of industries from west to east.
Objective:
Delimitate those areas that could be more affected by relocation
processes of high risk delocalization sectors in Catalonia

Geographic unit: Local Labour Systems –LLS – (aggregation of
municipalities according to commuting flows. Problem: Modifiable Areal
Unit Problem)
What fraction represents Catalonia in Spain in terms of…

Population: 15,47%

Total GDP: 18,43%

Employment in service sectors: 15,9%

Employment in industrial sectors: 25,04%
Source: INE, 2001
2. Data

Employment in each municipality of Catalonia with a 2-digit
level of sectoral disaggregation - NACE-Rev 1.1. (60 sectors),
2001 (Idescat)

Input-output table of Catalonia, 2001
2. Methodology
1.
Determine those sectors in Catalonia with a higher risk of delocalization
according to:
1.
2.
3.
2.
Existing literature
Closure of establishments between 2001 and 2005
Input-output relations
Compute for each risk sector and LLS the LOCATION QUOTIENTS
(employment data):
Yij
Lij 
Yi
Yj
i  1, ..., N; j  1,..., R
Y
Yij Employment in sector j and LLS i
Yi
Total employment in LLS i
Y j Total employment in sector j
Y Total employment in Catalonia
Lij >1: LLS i is more specialized in industry j than Catalonia
2. Methodology

Select high risk LLS according to:
1.
Lij  2 j   j
2. Using the LISA cluster map: select the significant high-high values!
BUT: Significant HH values do not correspond with those areas with
a higher location quotient!
3. Research problem:
Example: Manufacturing of textiles
4. Question
Is there any other technique in the
Exploratory Spatial Data Analysis to detect
the particular areas that form a cluster of
activity???